Kernel Measure of Multi-Sample Dissimilarity
Overview
Implementations of the kernel measure of multi-sample dissimilarity (KMD) between several samples using K-nearest neighbor graphs and minimum spanning trees. The KMD measures the dissimilarity between multiple samples, based on the observations from them. It converges to the population quantity (depending on the kernel) which is between 0 and 1. A small value indicates the multiple samples are from the same distribution, and a large value indicates the corresponding distributions are different. The population quantity is 0 if and only if all distributions are the same, and 1 if and only if all distributions are mutually singular. The package also implements the tests based on KMD for H0: the M distributions are equal against H1: not all the distributions are equal. Both permutation test and asymptotic test are available. These tests are consistent against all alternatives where at least two samples have different distributions. For more details on KMD and the associated tests, see Huang, Z. and B. Sen (2024) doi:10.1080/01621459.2023.2298036.
- Update for mlpack 4.8.0 API change.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-07-15
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 2
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 81%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing KMD adds 16 packages (13 with compiled code, 19 MB of source tarballs). Heaviest: data.table 5.7 MB, igraph 4.8 MB, mlpack 2.0 MB.
Code & Tests
People & History
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- 0.1.1Latest
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.02022-10-06
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-10-06
- Total releases
- 2 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.5.0
- Download size
- 7.7 KB
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